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Brett W. Bader Sandia Home
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Address

Brett W. Bader
Senior Member of Technical Staff
Data Analysis and Informatics Department
Sandia National Laboratories
P.O. Box 5800
Albuquerque, NM 87185-1318
Phone: 505-845-0514
Fax: 505-845-7442
Email: bwbader@sandia.gov
WWW: http://www.sandia.gov/~bwbader/


Professional Background

I started at Sandia National Laboratories in 2003 after earning a Ph.D. from the University of Colorado at Boulder under the guidance of Bobby Schnabel. I was awarded the John von Neumann postdoctoral research fellowship at Sandia in 2003, which funded my research in a variety of areas, including algorithms for nonlinear equations that incorporate higher-order tensors, multilinear algebra techniques applied to informatics, and reduced order modeling aimed at online optimal control. In 2005, I was promoted to Senior Member of Technical Staff.   More on my background...  See full CV...


Research Interests

Overall theme: Computational methods from the areas of multilinear algebra, machine learning, and optimization and their application to informatics, data mining, and engineering problems.
  • Tensor (or multiway array) decompositions
    PARAFAC, Tucker, DEDICOM, orthogonal decompositions, higher-order SVD (HOSVD)
     
  • Informatics and machine learning
     
    • Text analysis
      Multilingual document clustering, cross-language information retrieval, higher-order variants of latent semantic analysis (LSA), sentiment analysis, part of speech tagging
       
    • Social network analysis
      Community finding, semantic graphs, pattern detection, time graphs, collaborative filtering
       
    • Anomaly and pattern detection
      Heterogenous data, temporal data
       
    • Image analysis
      Hyperspectral and multispectral image analysis, remote sensing
       
  • Iterative methods for large-scale problems:
     
    • Nonlinear equations
      Newton's method, tensor methods, quasi-Newton methods
       
    • Linear systems
      Krylov subspace methods for linear systems, GMRES
       
    • Optimization
      Unconstrained and constrained minimization, PDE-constrained optimization, limited-memory quasi-Newton methods (e.g., BFGS)
       
    • Reduced-order modeling
      Proper orthogonal decomposition (POD), Krylov subspace techniques, optimization and optimal control
       
  • Computational biology
    Protein structure prediction
     
  • Software engineering
    Object-oriented software framework development, configuration management tools
     

Current and Recent Projects

  • Networks Grand Challenge
  • Data mining using tensor decompositions
  • MATLAB Tensor Toolbox
  • Data mining reading group (Sandia link only)
  • Reduced-order modeling for real-time optimal control
  • NOX: an object-oriented nonlinear solvers package
  • Trilinos: solver framework

  • Selected Publications

    See the complete list of abstracts

    Selected Presentations

    See my complete list of presentations

    Conference Schedule


    Educational and Professional Background

    My college education started at MIT, where I earned a B.S. and M.S in Chemical Engineering. After graduation, I started at the Dow Chemical Company where I worked on an on-line, real-time computational model of an ethylene plant for optimizing economic performance. That work inspired my interest in numerical methods and precipitated my return to graduate school. I enrolled in the Ph.D. program of the Department of Computer Science at the University of Colorado at Boulder. I initially worked for Richard Byrd and Bobby Schnabel on a project involving large-scale, global optimization of protein conformations - the so-called "protein folding" problem. Our research aimed at deriving the native protein structure by finding the global minimizer of physics-based computational model of the protein (i.e., a potential energy function). My Ph.D. thesis topic concerned the development of three "tensor-Krylov" methods for solving large-scale systems of nonlinear equations. These methods are based on including limited second-order information via a rank-1 tensor and perform well on ill-conditioned and singular problems. I earned my Ph.D. in 2003 under the guidance of Bobby Schnabel. Thereafter, I joined the staff of Sandia National Laboratories, where I was awarded the John von Neumann postdoctoral research fellowship. My research at Sandia has covered a variety of areas that stem from my interest in algorithms and higher-order methods. In September of 2005, I was promoted to Senior Member of Technical Staff in the Applied Computational Methods department. With subsequent internal reorganizations, I am currently in the department of Data Analysis and Informatics.


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